Overview

Dataset statistics

Number of variables17
Number of observations113
Missing cells467
Missing cells (%)24.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.1 KiB
Average record size in memory137.1 B

Variable types

Numeric5
Text7
Categorical1
DateTime3
Unsupported1

Alerts

airdate has constant value ""Constant
id is highly overall correlated with id_embeddedHigh correlation
id_embedded is highly overall correlated with id and 1 other fieldsHigh correlation
season is highly overall correlated with id_embeddedHigh correlation
number is highly overall correlated with typeHigh correlation
type is highly overall correlated with numberHigh correlation
type is highly imbalanced (80.8%)Imbalance
number has 5 (4.4%) missing valuesMissing
airtime has 67 (59.3%) missing valuesMissing
runtime has 7 (6.2%) missing valuesMissing
rating_average has 113 (100.0%) missing valuesMissing
medium has 91 (80.5%) missing valuesMissing
original has 91 (80.5%) missing valuesMissing
summary has 93 (82.3%) missing valuesMissing
id has unique valuesUnique
url has unique valuesUnique
_links_self has unique valuesUnique
rating_average is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-08-05 19:20:01.702909
Analysis finished2023-08-05 19:20:05.682117
Duration3.98 seconds
Software versionydata-profiling vv4.4.0
Download configurationconfig.json

Variables

id
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct113
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2454958.1
Minimum2367122
Maximum2607231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-08-05T14:20:05.771345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2367122
5-th percentile2397352
Q12440973
median2453930
Q32463753
95-th percentile2500617.6
Maximum2607231
Range240109
Interquartile range (IQR)22780

Descriptive statistics

Standard deviation35665.706
Coefficient of variation (CV)0.014528031
Kurtosis7.5621713
Mean2454958.1
Median Absolute Deviation (MAD)10780
Skewness1.7314364
Sum2.7741026 × 108
Variance1.2720426 × 109
MonotonicityNot monotonic
2023-08-05T14:20:05.945105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2452413 1
 
0.9%
2449312 1
 
0.9%
2464718 1
 
0.9%
2464717 1
 
0.9%
2464716 1
 
0.9%
2464715 1
 
0.9%
2464714 1
 
0.9%
2464713 1
 
0.9%
2464712 1
 
0.9%
2464711 1
 
0.9%
Other values (103) 103
91.2%
ValueCountFrequency (%)
2367122 1
0.9%
2380956 1
0.9%
2387353 1
0.9%
2391044 1
0.9%
2393403 1
0.9%
2393548 1
0.9%
2399888 1
0.9%
2404244 1
0.9%
2409570 1
0.9%
2413738 1
0.9%
ValueCountFrequency (%)
2607231 1
0.9%
2607230 1
0.9%
2603386 1
0.9%
2537086 1
0.9%
2517998 1
0.9%
2502102 1
0.9%
2499628 1
0.9%
2494231 1
0.9%
2494230 1
0.9%
2493494 1
0.9%

id_embedded
Real number (ℝ)

HIGH CORRELATION 

Distinct76
Distinct (%)67.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57894.761
Minimum2266
Maximum70186
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-08-05T14:20:06.135176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2266
5-th percentile15936.6
Q158174
median65081
Q366245
95-th percentile67101.4
Maximum70186
Range67920
Interquartile range (IQR)8071

Descriptive statistics

Standard deviation15192.963
Coefficient of variation (CV)0.26242379
Kurtosis4.5920267
Mean57894.761
Median Absolute Deviation (MAD)1167
Skewness-2.2628681
Sum6542108
Variance2.3082611 × 108
MonotonicityNot monotonic
2023-08-05T14:20:06.320382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
66245 15
 
13.3%
66113 6
 
5.3%
66248 6
 
5.3%
70186 2
 
1.8%
66103 2
 
1.8%
61632 2
 
1.8%
65894 2
 
1.8%
66153 2
 
1.8%
66162 2
 
1.8%
67120 2
 
1.8%
Other values (66) 72
63.7%
ValueCountFrequency (%)
2266 1
0.9%
4962 1
0.9%
6146 1
0.9%
10892 1
0.9%
13381 1
0.9%
13392 1
0.9%
17633 1
0.9%
18971 1
0.9%
38429 1
0.9%
39114 1
0.9%
ValueCountFrequency (%)
70186 2
 
1.8%
68448 1
 
0.9%
67883 1
 
0.9%
67120 2
 
1.8%
67089 1
 
0.9%
66819 1
 
0.9%
66441 1
 
0.9%
66248 6
 
5.3%
66245 15
13.3%
66244 2
 
1.8%

url
Text

UNIQUE 

Distinct113
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-08-05T14:20:06.615409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length145
Median length101
Mean length79.044248
Min length62

Characters and Unicode

Total characters8932
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique113 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/2452413/nu-pogodi-kanikuly-1x20-konki-i-sanki
2nd rowhttps://www.tvmaze.com/episodes/2452414/troe-iz-prostokvasino-4x08-odni-doma
3rd rowhttps://www.tvmaze.com/episodes/2417448/vampiry-srednej-polosy-2x02-seria-2
4th rowhttps://www.tvmaze.com/episodes/2422259/trudnye-podrostki-realnost-2x19-seria-19
5th rowhttps://www.tvmaze.com/episodes/2422260/trudnye-podrostki-realnost-2x20-seria-20
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/2452413/nu-pogodi-kanikuly-1x20-konki-i-sanki 1
 
0.9%
https://www.tvmaze.com/episodes/2452414/troe-iz-prostokvasino-4x08-odni-doma 1
 
0.9%
https://www.tvmaze.com/episodes/2417448/vampiry-srednej-polosy-2x02-seria-2 1
 
0.9%
https://www.tvmaze.com/episodes/2422259/trudnye-podrostki-realnost-2x19-seria-19 1
 
0.9%
https://www.tvmaze.com/episodes/2422260/trudnye-podrostki-realnost-2x20-seria-20 1
 
0.9%
https://www.tvmaze.com/episodes/2452403/martyskiny-1x18-novogodnij-sekret 1
 
0.9%
https://www.tvmaze.com/episodes/2440096/a-slezu-za-toboj-1x07-seria-7 1
 
0.9%
https://www.tvmaze.com/episodes/2417324/wu-shen-zhu-zai-1x292-episode-292 1
 
0.9%
https://www.tvmaze.com/episodes/2437455/wan-jie-du-zun-2x38-episode-88 1
 
0.9%
https://www.tvmaze.com/episodes/2447403/wo-kao-chongzhi-dang-wudi-1x57-no57 1
 
0.9%
Other values (103) 103
91.2%
2023-08-05T14:20:07.100093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 779
 
8.7%
- 706
 
7.9%
/ 565
 
6.3%
s 557
 
6.2%
t 514
 
5.8%
o 512
 
5.7%
w 397
 
4.4%
i 376
 
4.2%
a 357
 
4.0%
p 336
 
3.8%
Other values (30) 3833
42.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6009
67.3%
Decimal Number 1313
 
14.7%
Other Punctuation 904
 
10.1%
Dash Punctuation 706
 
7.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 779
13.0%
s 557
 
9.3%
t 514
 
8.6%
o 512
 
8.5%
w 397
 
6.6%
i 376
 
6.3%
a 357
 
5.9%
p 336
 
5.6%
m 294
 
4.9%
d 266
 
4.4%
Other values (16) 1621
27.0%
Decimal Number
ValueCountFrequency (%)
2 257
19.6%
1 230
17.5%
4 214
16.3%
0 137
10.4%
5 110
8.4%
3 96
 
7.3%
6 78
 
5.9%
7 73
 
5.6%
9 61
 
4.6%
8 57
 
4.3%
Other Punctuation
ValueCountFrequency (%)
/ 565
62.5%
. 226
 
25.0%
: 113
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
- 706
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6009
67.3%
Common 2923
32.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 779
13.0%
s 557
 
9.3%
t 514
 
8.6%
o 512
 
8.5%
w 397
 
6.6%
i 376
 
6.3%
a 357
 
5.9%
p 336
 
5.6%
m 294
 
4.9%
d 266
 
4.4%
Other values (16) 1621
27.0%
Common
ValueCountFrequency (%)
- 706
24.2%
/ 565
19.3%
2 257
 
8.8%
1 230
 
7.9%
. 226
 
7.7%
4 214
 
7.3%
0 137
 
4.7%
: 113
 
3.9%
5 110
 
3.8%
3 96
 
3.3%
Other values (4) 269
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8932
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 779
 
8.7%
- 706
 
7.9%
/ 565
 
6.3%
s 557
 
6.2%
t 514
 
5.8%
o 512
 
5.7%
w 397
 
4.4%
i 376
 
4.2%
a 357
 
4.0%
p 336
 
3.8%
Other values (30) 3833
42.9%

name
Text

Distinct71
Distinct (%)62.8%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-08-05T14:20:07.472320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length93
Median length85
Mean length14.362832
Min length3

Characters and Unicode

Total characters1623
Distinct characters125
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)47.8%

Sample

1st rowКоньки и санки
2nd rowОдни дома
3rd rowСерия 2
4th rowСерия 19
5th rowСерия 20
ValueCountFrequency (%)
episode 66
 
21.4%
the 7
 
2.3%
15 6
 
1.9%
2 6
 
1.9%
5 5
 
1.6%
3 5
 
1.6%
10 5
 
1.6%
13 5
 
1.6%
6 5
 
1.6%
4
 
1.3%
Other values (162) 194
63.0%
2023-08-05T14:20:08.033586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
195
 
12.0%
e 133
 
8.2%
s 101
 
6.2%
i 98
 
6.0%
o 94
 
5.8%
d 77
 
4.7%
E 76
 
4.7%
p 74
 
4.6%
a 50
 
3.1%
1 43
 
2.6%
Other values (115) 682
42.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1002
61.7%
Uppercase Letter 255
 
15.7%
Space Separator 195
 
12.0%
Decimal Number 142
 
8.7%
Other Punctuation 23
 
1.4%
Dash Punctuation 3
 
0.2%
Other Symbol 1
 
0.1%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 133
13.3%
s 101
 
10.1%
i 98
 
9.8%
o 94
 
9.4%
d 77
 
7.7%
p 74
 
7.4%
a 50
 
5.0%
r 26
 
2.6%
l 26
 
2.6%
и 24
 
2.4%
Other values (46) 299
29.8%
Uppercase Letter
ValueCountFrequency (%)
E 76
29.8%
T 14
 
5.5%
Л 9
 
3.5%
О 8
 
3.1%
M 8
 
3.1%
A 8
 
3.1%
Е 7
 
2.7%
К 7
 
2.7%
N 7
 
2.7%
F 6
 
2.4%
Other values (34) 105
41.2%
Decimal Number
ValueCountFrequency (%)
1 43
30.3%
2 22
15.5%
3 13
 
9.2%
5 13
 
9.2%
6 11
 
7.7%
4 11
 
7.7%
0 10
 
7.0%
7 7
 
4.9%
8 6
 
4.2%
9 6
 
4.2%
Other Punctuation
ValueCountFrequency (%)
. 5
21.7%
, 4
17.4%
: 3
13.0%
? 3
13.0%
& 2
 
8.7%
# 2
 
8.7%
! 2
 
8.7%
/ 1
 
4.3%
' 1
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 2
66.7%
1
33.3%
Space Separator
ValueCountFrequency (%)
195
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1000
61.6%
Common 366
 
22.6%
Cyrillic 257
 
15.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 133
13.3%
s 101
10.1%
i 98
 
9.8%
o 94
 
9.4%
d 77
 
7.7%
E 76
 
7.6%
p 74
 
7.4%
a 50
 
5.0%
r 26
 
2.6%
l 26
 
2.6%
Other values (40) 245
24.5%
Cyrillic
ValueCountFrequency (%)
и 24
 
9.3%
о 16
 
6.2%
е 14
 
5.4%
т 12
 
4.7%
а 12
 
4.7%
в 12
 
4.7%
р 11
 
4.3%
к 10
 
3.9%
Л 9
 
3.5%
О 8
 
3.1%
Other values (40) 129
50.2%
Common
ValueCountFrequency (%)
195
53.3%
1 43
 
11.7%
2 22
 
6.0%
3 13
 
3.6%
5 13
 
3.6%
6 11
 
3.0%
4 11
 
3.0%
0 10
 
2.7%
7 7
 
1.9%
8 6
 
1.6%
Other values (15) 35
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1361
83.9%
Cyrillic 257
 
15.8%
None 3
 
0.2%
Punctuation 1
 
0.1%
Letterlike Symbols 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
195
14.3%
e 133
 
9.8%
s 101
 
7.4%
i 98
 
7.2%
o 94
 
6.9%
d 77
 
5.7%
E 76
 
5.6%
p 74
 
5.4%
a 50
 
3.7%
1 43
 
3.2%
Other values (60) 420
30.9%
Cyrillic
ValueCountFrequency (%)
и 24
 
9.3%
о 16
 
6.2%
е 14
 
5.4%
т 12
 
4.7%
а 12
 
4.7%
в 12
 
4.7%
р 11
 
4.3%
к 10
 
3.9%
Л 9
 
3.5%
О 8
 
3.1%
Other values (40) 129
50.2%
Punctuation
ValueCountFrequency (%)
1
100.0%
Letterlike Symbols
ValueCountFrequency (%)
1
100.0%
None
ValueCountFrequency (%)
í 1
33.3%
ú 1
33.3%
ó 1
33.3%

season
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.62832
Minimum1
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-08-05T14:20:08.191175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile2022
Maximum2022
Range2021
Interquartile range (IQR)1

Descriptive statistics

Standard deviation489.00451
Coefficient of variation (CV)3.8314734
Kurtosis11.77329
Mean127.62832
Median Absolute Deviation (MAD)0
Skewness3.6828675
Sum14422
Variance239125.41
MonotonicityNot monotonic
2023-08-05T14:20:08.331428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1 76
67.3%
2 11
 
9.7%
2022 7
 
6.2%
5 5
 
4.4%
4 4
 
3.5%
9 3
 
2.7%
6 1
 
0.9%
46 1
 
0.9%
14 1
 
0.9%
7 1
 
0.9%
Other values (3) 3
 
2.7%
ValueCountFrequency (%)
1 76
67.3%
2 11
 
9.7%
3 1
 
0.9%
4 4
 
3.5%
5 5
 
4.4%
6 1
 
0.9%
7 1
 
0.9%
9 3
 
2.7%
10 1
 
0.9%
14 1
 
0.9%
ValueCountFrequency (%)
2022 7
6.2%
46 1
 
0.9%
16 1
 
0.9%
14 1
 
0.9%
10 1
 
0.9%
9 3
2.7%
7 1
 
0.9%
6 1
 
0.9%
5 5
4.4%
4 4
3.5%

number
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct35
Distinct (%)32.4%
Missing5
Missing (%)4.4%
Infinite0
Infinite (%)0.0%
Mean22.944444
Minimum1
Maximum292
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-08-05T14:20:08.474099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q15
median10.5
Q317
95-th percentile62.2
Maximum292
Range291
Interquartile range (IQR)12

Descriptive statistics

Standard deviation45.36206
Coefficient of variation (CV)1.9770389
Kurtosis20.994083
Mean22.944444
Median Absolute Deviation (MAD)5.5
Skewness4.4217596
Sum2478
Variance2057.7165
MonotonicityNot monotonic
2023-08-05T14:20:08.625852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
2 8
 
7.1%
5 7
 
6.2%
15 7
 
6.2%
3 6
 
5.3%
6 6
 
5.3%
8 6
 
5.3%
51 5
 
4.4%
4 5
 
4.4%
13 5
 
4.4%
10 5
 
4.4%
Other values (25) 48
42.5%
(Missing) 5
 
4.4%
ValueCountFrequency (%)
1 4
3.5%
2 8
7.1%
3 6
5.3%
4 5
4.4%
5 7
6.2%
6 6
5.3%
7 3
 
2.7%
8 6
5.3%
9 4
3.5%
10 5
4.4%
ValueCountFrequency (%)
292 1
 
0.9%
246 1
 
0.9%
243 1
 
0.9%
142 1
 
0.9%
101 1
 
0.9%
65 1
 
0.9%
57 1
 
0.9%
56 1
 
0.9%
51 5
4.4%
49 1
 
0.9%

type
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
regular
108 
significant_special
 
3
insignificant_special
 
2

Length

Max length21
Median length7
Mean length7.5663717
Min length7

Characters and Unicode

Total characters855
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular 108
95.6%
significant_special 3
 
2.7%
insignificant_special 2
 
1.8%

Length

2023-08-05T14:20:08.792010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-05T14:20:08.918282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
regular 108
95.6%
significant_special 3
 
2.7%
insignificant_special 2
 
1.8%

Most occurring characters

ValueCountFrequency (%)
r 216
25.3%
a 118
13.8%
e 113
13.2%
g 113
13.2%
l 113
13.2%
u 108
12.6%
i 22
 
2.6%
n 12
 
1.4%
s 10
 
1.2%
c 10
 
1.2%
Other values (4) 20
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 850
99.4%
Connector Punctuation 5
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 216
25.4%
a 118
13.9%
e 113
13.3%
g 113
13.3%
l 113
13.3%
u 108
12.7%
i 22
 
2.6%
n 12
 
1.4%
s 10
 
1.2%
c 10
 
1.2%
Other values (3) 15
 
1.8%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 850
99.4%
Common 5
 
0.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 216
25.4%
a 118
13.9%
e 113
13.3%
g 113
13.3%
l 113
13.3%
u 108
12.7%
i 22
 
2.6%
n 12
 
1.4%
s 10
 
1.2%
c 10
 
1.2%
Other values (3) 15
 
1.8%
Common
ValueCountFrequency (%)
_ 5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 855
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r 216
25.3%
a 118
13.8%
e 113
13.2%
g 113
13.2%
l 113
13.2%
u 108
12.6%
i 22
 
2.6%
n 12
 
1.4%
s 10
 
1.2%
c 10
 
1.2%
Other values (4) 20
 
2.3%

airdate
Date

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Minimum2022-12-20 00:00:00
Maximum2022-12-20 00:00:00
2023-08-05T14:20:09.022046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:20:09.131826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

airtime
Date

MISSING 

Distinct16
Distinct (%)34.8%
Missing67
Missing (%)59.3%
Memory size1.0 KiB
Minimum2023-08-05 00:00:00
Maximum2023-08-05 22:30:00
2023-08-05T14:20:09.240921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:20:09.378021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
Distinct22
Distinct (%)19.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Minimum2022-12-19 22:00:00+00:00
Maximum2022-12-21 02:00:00+00:00
2023-08-05T14:20:09.516500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:20:09.651566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)

runtime
Real number (ℝ)

MISSING 

Distinct36
Distinct (%)34.0%
Missing7
Missing (%)6.2%
Infinite0
Infinite (%)0.0%
Mean32.830189
Minimum2
Maximum165
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-08-05T14:20:09.784299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5
Q112
median24.5
Q345
95-th percentile72
Maximum165
Range163
Interquartile range (IQR)33

Descriptive statistics

Standard deviation26.810969
Coefficient of variation (CV)0.81665594
Kurtosis5.2860553
Mean32.830189
Median Absolute Deviation (MAD)17.5
Skewness1.719058
Sum3480
Variance718.82803
MonotonicityNot monotonic
2023-08-05T14:20:09.949495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
15 16
14.2%
45 15
13.3%
5 8
 
7.1%
10 8
 
7.1%
60 6
 
5.3%
42 4
 
3.5%
40 4
 
3.5%
9 4
 
3.5%
57 3
 
2.7%
20 3
 
2.7%
Other values (26) 35
31.0%
(Missing) 7
 
6.2%
ValueCountFrequency (%)
2 1
 
0.9%
3 1
 
0.9%
5 8
7.1%
7 3
 
2.7%
8 1
 
0.9%
9 4
 
3.5%
10 8
7.1%
12 2
 
1.8%
15 16
14.2%
17 1
 
0.9%
ValueCountFrequency (%)
165 1
 
0.9%
125 1
 
0.9%
90 2
 
1.8%
73 1
 
0.9%
72 2
 
1.8%
70 1
 
0.9%
66 1
 
0.9%
62 1
 
0.9%
60 6
5.3%
59 1
 
0.9%

rating_average
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing113
Missing (%)100.0%
Memory size1.0 KiB

medium
Text

MISSING 

Distinct22
Distinct (%)100.0%
Missing91
Missing (%)80.5%
Memory size1.0 KiB
2023-08-05T14:20:10.208624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length73
Median length73
Mean length73
Min length73

Characters and Unicode

Total characters1606
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_landscape/436/1090584.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/436/1090824.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/438/1095190.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/436/1090270.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/436/1090265.jpg
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/436/1090584.jpg 1
 
4.5%
https://static.tvmaze.com/uploads/images/medium_landscape/436/1090245.jpg 1
 
4.5%
https://static.tvmaze.com/uploads/images/medium_landscape/438/1095190.jpg 1
 
4.5%
https://static.tvmaze.com/uploads/images/medium_landscape/436/1090270.jpg 1
 
4.5%
https://static.tvmaze.com/uploads/images/medium_landscape/436/1090265.jpg 1
 
4.5%
https://static.tvmaze.com/uploads/images/medium_landscape/455/1139298.jpg 1
 
4.5%
https://static.tvmaze.com/uploads/images/medium_landscape/436/1090434.jpg 1
 
4.5%
https://static.tvmaze.com/uploads/images/medium_landscape/436/1090411.jpg 1
 
4.5%
https://static.tvmaze.com/uploads/images/medium_landscape/436/1090256.jpg 1
 
4.5%
https://static.tvmaze.com/uploads/images/medium_landscape/436/1090257.jpg 1
 
4.5%
Other values (12) 12
54.5%
2023-08-05T14:20:10.594712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 154
 
9.6%
a 132
 
8.2%
m 110
 
6.8%
s 110
 
6.8%
t 110
 
6.8%
p 88
 
5.5%
e 88
 
5.5%
. 66
 
4.1%
d 66
 
4.1%
c 66
 
4.1%
Other values (22) 616
38.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1122
69.9%
Other Punctuation 242
 
15.1%
Decimal Number 220
 
13.7%
Connector Punctuation 22
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 132
11.8%
m 110
9.8%
s 110
9.8%
t 110
9.8%
p 88
 
7.8%
e 88
 
7.8%
d 66
 
5.9%
c 66
 
5.9%
i 66
 
5.9%
g 44
 
3.9%
Other values (8) 242
21.6%
Decimal Number
ValueCountFrequency (%)
0 40
18.2%
4 39
17.7%
1 33
15.0%
3 25
11.4%
9 24
10.9%
6 20
9.1%
5 13
 
5.9%
2 12
 
5.5%
8 8
 
3.6%
7 6
 
2.7%
Other Punctuation
ValueCountFrequency (%)
/ 154
63.6%
. 66
27.3%
: 22
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_ 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1122
69.9%
Common 484
30.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 132
11.8%
m 110
9.8%
s 110
9.8%
t 110
9.8%
p 88
 
7.8%
e 88
 
7.8%
d 66
 
5.9%
c 66
 
5.9%
i 66
 
5.9%
g 44
 
3.9%
Other values (8) 242
21.6%
Common
ValueCountFrequency (%)
/ 154
31.8%
. 66
13.6%
0 40
 
8.3%
4 39
 
8.1%
1 33
 
6.8%
3 25
 
5.2%
9 24
 
5.0%
_ 22
 
4.5%
: 22
 
4.5%
6 20
 
4.1%
Other values (4) 39
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1606
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 154
 
9.6%
a 132
 
8.2%
m 110
 
6.8%
s 110
 
6.8%
t 110
 
6.8%
p 88
 
5.5%
e 88
 
5.5%
. 66
 
4.1%
d 66
 
4.1%
c 66
 
4.1%
Other values (22) 616
38.4%

original
Text

MISSING 

Distinct22
Distinct (%)100.0%
Missing91
Missing (%)80.5%
Memory size1.0 KiB
2023-08-05T14:20:10.848823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length75
Median length75
Mean length75
Min length75

Characters and Unicode

Total characters1650
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/436/1090584.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/436/1090824.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/438/1095190.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/436/1090270.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/436/1090265.jpg
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/436/1090584.jpg 1
 
4.5%
https://static.tvmaze.com/uploads/images/original_untouched/436/1090245.jpg 1
 
4.5%
https://static.tvmaze.com/uploads/images/original_untouched/438/1095190.jpg 1
 
4.5%
https://static.tvmaze.com/uploads/images/original_untouched/436/1090270.jpg 1
 
4.5%
https://static.tvmaze.com/uploads/images/original_untouched/436/1090265.jpg 1
 
4.5%
https://static.tvmaze.com/uploads/images/original_untouched/455/1139298.jpg 1
 
4.5%
https://static.tvmaze.com/uploads/images/original_untouched/436/1090434.jpg 1
 
4.5%
https://static.tvmaze.com/uploads/images/original_untouched/436/1090411.jpg 1
 
4.5%
https://static.tvmaze.com/uploads/images/original_untouched/436/1090256.jpg 1
 
4.5%
https://static.tvmaze.com/uploads/images/original_untouched/436/1090257.jpg 1
 
4.5%
Other values (12) 12
54.5%
2023-08-05T14:20:11.220793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 154
 
9.3%
t 132
 
8.0%
a 110
 
6.7%
s 88
 
5.3%
i 88
 
5.3%
o 88
 
5.3%
p 66
 
4.0%
c 66
 
4.0%
. 66
 
4.0%
g 66
 
4.0%
Other values (23) 726
44.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1166
70.7%
Other Punctuation 242
 
14.7%
Decimal Number 220
 
13.3%
Connector Punctuation 22
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 132
 
11.3%
a 110
 
9.4%
s 88
 
7.5%
i 88
 
7.5%
o 88
 
7.5%
p 66
 
5.7%
c 66
 
5.7%
g 66
 
5.7%
m 66
 
5.7%
e 66
 
5.7%
Other values (9) 330
28.3%
Decimal Number
ValueCountFrequency (%)
0 40
18.2%
4 39
17.7%
1 33
15.0%
3 25
11.4%
9 24
10.9%
6 20
9.1%
5 13
 
5.9%
2 12
 
5.5%
8 8
 
3.6%
7 6
 
2.7%
Other Punctuation
ValueCountFrequency (%)
/ 154
63.6%
. 66
27.3%
: 22
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_ 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1166
70.7%
Common 484
29.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 132
 
11.3%
a 110
 
9.4%
s 88
 
7.5%
i 88
 
7.5%
o 88
 
7.5%
p 66
 
5.7%
c 66
 
5.7%
g 66
 
5.7%
m 66
 
5.7%
e 66
 
5.7%
Other values (9) 330
28.3%
Common
ValueCountFrequency (%)
/ 154
31.8%
. 66
13.6%
0 40
 
8.3%
4 39
 
8.1%
1 33
 
6.8%
3 25
 
5.2%
9 24
 
5.0%
: 22
 
4.5%
_ 22
 
4.5%
6 20
 
4.1%
Other values (4) 39
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1650
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 154
 
9.3%
t 132
 
8.0%
a 110
 
6.7%
s 88
 
5.3%
i 88
 
5.3%
o 88
 
5.3%
p 66
 
4.0%
c 66
 
4.0%
. 66
 
4.0%
g 66
 
4.0%
Other values (23) 726
44.0%

_links_self
Text

UNIQUE 

Distinct113
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-08-05T14:20:11.587749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters4407
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique113 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2452413
2nd rowhttps://api.tvmaze.com/episodes/2452414
3rd rowhttps://api.tvmaze.com/episodes/2417448
4th rowhttps://api.tvmaze.com/episodes/2422259
5th rowhttps://api.tvmaze.com/episodes/2422260
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/2452413 1
 
0.9%
https://api.tvmaze.com/episodes/2452414 1
 
0.9%
https://api.tvmaze.com/episodes/2417448 1
 
0.9%
https://api.tvmaze.com/episodes/2422259 1
 
0.9%
https://api.tvmaze.com/episodes/2422260 1
 
0.9%
https://api.tvmaze.com/episodes/2452403 1
 
0.9%
https://api.tvmaze.com/episodes/2440096 1
 
0.9%
https://api.tvmaze.com/episodes/2417324 1
 
0.9%
https://api.tvmaze.com/episodes/2437455 1
 
0.9%
https://api.tvmaze.com/episodes/2447403 1
 
0.9%
Other values (103) 103
91.2%
2023-08-05T14:20:11.933486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 452
 
10.3%
p 339
 
7.7%
s 339
 
7.7%
e 339
 
7.7%
t 339
 
7.7%
o 226
 
5.1%
a 226
 
5.1%
i 226
 
5.1%
. 226
 
5.1%
m 226
 
5.1%
Other values (16) 1469
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2825
64.1%
Other Punctuation 791
 
17.9%
Decimal Number 791
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p 339
12.0%
s 339
12.0%
e 339
12.0%
t 339
12.0%
o 226
8.0%
a 226
8.0%
i 226
8.0%
m 226
8.0%
h 113
 
4.0%
d 113
 
4.0%
Other values (3) 339
12.0%
Decimal Number
ValueCountFrequency (%)
4 183
23.1%
2 164
20.7%
5 74
9.4%
3 68
 
8.6%
7 59
 
7.5%
1 53
 
6.7%
6 52
 
6.6%
0 50
 
6.3%
9 45
 
5.7%
8 43
 
5.4%
Other Punctuation
ValueCountFrequency (%)
/ 452
57.1%
. 226
28.6%
: 113
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 2825
64.1%
Common 1582
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 452
28.6%
. 226
14.3%
4 183
11.6%
2 164
 
10.4%
: 113
 
7.1%
5 74
 
4.7%
3 68
 
4.3%
7 59
 
3.7%
1 53
 
3.4%
6 52
 
3.3%
Other values (3) 138
 
8.7%
Latin
ValueCountFrequency (%)
p 339
12.0%
s 339
12.0%
e 339
12.0%
t 339
12.0%
o 226
8.0%
a 226
8.0%
i 226
8.0%
m 226
8.0%
h 113
 
4.0%
d 113
 
4.0%
Other values (3) 339
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4407
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 452
 
10.3%
p 339
 
7.7%
s 339
 
7.7%
e 339
 
7.7%
t 339
 
7.7%
o 226
 
5.1%
a 226
 
5.1%
i 226
 
5.1%
. 226
 
5.1%
m 226
 
5.1%
Other values (16) 1469
33.3%
Distinct76
Distinct (%)67.3%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-08-05T14:20:12.204333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length34
Mean length33.973451
Min length33

Characters and Unicode

Total characters3839
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)53.1%

Sample

1st rowhttps://api.tvmaze.com/shows/59537
2nd rowhttps://api.tvmaze.com/shows/10892
3rd rowhttps://api.tvmaze.com/shows/46433
4th rowhttps://api.tvmaze.com/shows/59071
5th rowhttps://api.tvmaze.com/shows/59071
ValueCountFrequency (%)
https://api.tvmaze.com/shows/66245 15
 
13.3%
https://api.tvmaze.com/shows/66248 6
 
5.3%
https://api.tvmaze.com/shows/66113 6
 
5.3%
https://api.tvmaze.com/shows/67120 2
 
1.8%
https://api.tvmaze.com/shows/59878 2
 
1.8%
https://api.tvmaze.com/shows/59071 2
 
1.8%
https://api.tvmaze.com/shows/59587 2
 
1.8%
https://api.tvmaze.com/shows/66066 2
 
1.8%
https://api.tvmaze.com/shows/66244 2
 
1.8%
https://api.tvmaze.com/shows/39145 2
 
1.8%
Other values (66) 72
63.7%
2023-08-05T14:20:12.619385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 452
 
11.8%
s 339
 
8.8%
t 339
 
8.8%
h 226
 
5.9%
p 226
 
5.9%
a 226
 
5.9%
. 226
 
5.9%
o 226
 
5.9%
m 226
 
5.9%
6 142
 
3.7%
Other values (16) 1211
31.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2486
64.8%
Other Punctuation 791
 
20.6%
Decimal Number 562
 
14.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 339
13.6%
t 339
13.6%
h 226
9.1%
p 226
9.1%
a 226
9.1%
o 226
9.1%
m 226
9.1%
e 113
 
4.5%
w 113
 
4.5%
c 113
 
4.5%
Other values (3) 339
13.6%
Decimal Number
ValueCountFrequency (%)
6 142
25.3%
4 77
13.7%
5 56
 
10.0%
1 53
 
9.4%
2 49
 
8.7%
3 45
 
8.0%
9 40
 
7.1%
8 38
 
6.8%
0 32
 
5.7%
7 30
 
5.3%
Other Punctuation
ValueCountFrequency (%)
/ 452
57.1%
. 226
28.6%
: 113
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 2486
64.8%
Common 1353
35.2%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 452
33.4%
. 226
16.7%
6 142
 
10.5%
: 113
 
8.4%
4 77
 
5.7%
5 56
 
4.1%
1 53
 
3.9%
2 49
 
3.6%
3 45
 
3.3%
9 40
 
3.0%
Other values (3) 100
 
7.4%
Latin
ValueCountFrequency (%)
s 339
13.6%
t 339
13.6%
h 226
9.1%
p 226
9.1%
a 226
9.1%
o 226
9.1%
m 226
9.1%
e 113
 
4.5%
w 113
 
4.5%
c 113
 
4.5%
Other values (3) 339
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3839
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 452
 
11.8%
s 339
 
8.8%
t 339
 
8.8%
h 226
 
5.9%
p 226
 
5.9%
a 226
 
5.9%
. 226
 
5.9%
o 226
 
5.9%
m 226
 
5.9%
6 142
 
3.7%
Other values (16) 1211
31.5%

summary
Text

MISSING 

Distinct20
Distinct (%)100.0%
Missing93
Missing (%)82.3%
Memory size1.0 KiB
2023-08-05T14:20:12.886280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length727
Median length166
Mean length278.8
Min length76

Characters and Unicode

Total characters5576
Distinct characters74
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)100.0%

Sample

1st row<p>When the extended family from the country and the beach gathers, it can result in complete dialect confusion. Today, it is important to understand as much as possible.</p>
2nd row<p>The department store Jonass has changed from a credit to a luxury department store - and Vicky is promoted to department manager. A lot has happened in her private life too: She is the mother of three-year-old Hanni and has a new partner at her side in Wilhelm, who is now even proposing to her. Harry and Helene are returning from the States where they have been for the past three years. Helene has accepted a position at the Charité and Harry has decided to get a record deal. But back home, Harry longs for Vicky. In recent years she has never answered his letters. Still, his feelings for her haven't changed...</p>
3rd row<p>Jon, Jon and Dan answer all of your burning questions about 2024, the Democratic party, the White Lotus, Taylor Swift, and more.</p>
4th row<p>There is a term "complex issues" in the lexicon of diplomacy. These are long-standing conflicts and painful problems in relations between countries and peoples. These are the "difficult issues" that make up Russia's relations with the Baltic states.<br /><br />On the one hand, this is the history of their accession to the USSR during Stalin's time. On the other hand, the problem of the rights of the Russian-speaking minority. Recent events have only aggravated everything — Latvia, Lithuania and Estonia occupy the toughest position among the EU countries. The story of the "Rain"* is another confirmation. <br /><br />In general, it's time to figure out — why did this happen? And where will this neighborhood lead?</p>
5th row<p>John Oates (Hall &amp; Oates) joins us this week to share his experience in the music industry and the ups and downs that come with being in a Rock &amp; Roll Hall of Fame inducted, multi million record selling duo like Hall &amp; Oates. John opens up on how he was able to pull himself out of the spiral his life was in during the late 80's as he wanted to change his image, was dealing with a divorce, and found out that he was being hoodwinked by Wall Street money managers. We also get into the mental health messaging that John includes in his music, who he was most excited to perform with, and some unfortunate things to happen on stage while he was performing.</p>
ValueCountFrequency (%)
the 56
 
6.0%
to 33
 
3.5%
and 32
 
3.4%
of 19
 
2.0%
a 19
 
2.0%
in 18
 
1.9%
is 14
 
1.5%
has 11
 
1.2%
her 10
 
1.1%
his 10
 
1.1%
Other values (521) 717
76.4%
2023-08-05T14:20:13.305578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
916
16.4%
e 523
 
9.4%
t 381
 
6.8%
a 348
 
6.2%
n 330
 
5.9%
i 310
 
5.6%
o 306
 
5.5%
s 287
 
5.1%
h 243
 
4.4%
r 242
 
4.3%
Other values (64) 1690
30.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4214
75.6%
Space Separator 919
 
16.5%
Uppercase Letter 168
 
3.0%
Other Punctuation 165
 
3.0%
Math Symbol 88
 
1.6%
Dash Punctuation 14
 
0.3%
Decimal Number 6
 
0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 523
12.4%
t 381
 
9.0%
a 348
 
8.3%
n 330
 
7.8%
i 310
 
7.4%
o 306
 
7.3%
s 287
 
6.8%
h 243
 
5.8%
r 242
 
5.7%
l 182
 
4.3%
Other values (18) 1062
25.2%
Uppercase Letter
ValueCountFrequency (%)
S 21
12.5%
H 18
 
10.7%
J 14
 
8.3%
T 14
 
8.3%
A 13
 
7.7%
R 9
 
5.4%
W 8
 
4.8%
M 8
 
4.8%
B 8
 
4.8%
L 6
 
3.6%
Other values (13) 49
29.2%
Other Punctuation
ValueCountFrequency (%)
. 56
33.9%
, 45
27.3%
/ 24
14.5%
' 17
 
10.3%
" 6
 
3.6%
; 4
 
2.4%
? 4
 
2.4%
& 3
 
1.8%
: 3
 
1.8%
! 2
 
1.2%
Decimal Number
ValueCountFrequency (%)
2 2
33.3%
0 2
33.3%
8 1
16.7%
4 1
16.7%
Space Separator
ValueCountFrequency (%)
916
99.7%
  3
 
0.3%
Math Symbol
ValueCountFrequency (%)
< 44
50.0%
> 44
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
85.7%
2
 
14.3%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4382
78.6%
Common 1194
 
21.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 523
11.9%
t 381
 
8.7%
a 348
 
7.9%
n 330
 
7.5%
i 310
 
7.1%
o 306
 
7.0%
s 287
 
6.5%
h 243
 
5.5%
r 242
 
5.5%
l 182
 
4.2%
Other values (41) 1230
28.1%
Common
ValueCountFrequency (%)
916
76.7%
. 56
 
4.7%
, 45
 
3.8%
< 44
 
3.7%
> 44
 
3.7%
/ 24
 
2.0%
' 17
 
1.4%
- 12
 
1.0%
" 6
 
0.5%
; 4
 
0.3%
Other values (13) 26
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5569
99.9%
None 5
 
0.1%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
916
16.4%
e 523
 
9.4%
t 381
 
6.8%
a 348
 
6.2%
n 330
 
5.9%
i 310
 
5.6%
o 306
 
5.5%
s 287
 
5.2%
h 243
 
4.4%
r 242
 
4.3%
Other values (60) 1683
30.2%
None
ValueCountFrequency (%)
  3
60.0%
ü 1
 
20.0%
é 1
 
20.0%
Punctuation
ValueCountFrequency (%)
2
100.0%

Interactions

2023-08-05T14:20:04.415490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:20:02.177455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:20:02.713124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:20:03.275637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:20:03.874207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:20:04.514482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:20:02.273992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:20:02.825774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:20:03.389284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:20:03.988683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:20:04.619885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:20:02.379617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:20:02.932054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:20:03.506639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:20:04.098763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:20:04.730680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:20:02.495384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:20:03.042350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:20:03.627252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:20:04.208479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:20:04.840156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:20:02.597940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:20:03.147231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:20:03.751931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T14:20:04.308722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-08-05T14:20:13.420273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
idid_embeddedseasonnumberruntimetype
id1.0000.674-0.282-0.200-0.2760.000
id_embedded0.6741.000-0.757-0.393-0.2770.268
season-0.282-0.7571.0000.2050.1860.000
number-0.200-0.3930.2051.000-0.0431.000
runtime-0.276-0.2770.186-0.0431.0000.000
type0.0000.2680.0001.0000.0001.000

Missing values

2023-08-05T14:20:05.179904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-08-05T14:20:05.435738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-08-05T14:20:05.602529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

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